Publication in Physical Review Applied: “Designing fast quantum gates using optimal control with a reinforcement-learning ansatz”
Our recent work, by Bijita Sarma and Michael J. Hartmann, has been published today in Physical Review Applied.
In this project, we successfully used reinforcement learning to design quantum controls that achieve very fast two-qubit gates on a transmon tunable coupler circuit. Our work showcases the potential of combining machine-learning with quantum computing platforms to solve complex design challenges.